Sepsis is a complex clinical syndrome caused by a dysregulated host immune response to infection. This study aimed to identify a competing endogenous RNA (ceRNA) network that can greatly contribute to understanding the pathophysiological process of sepsis and determining sepsis biomarkers. The GSE100159, GSE65682, GSE167363, and GSE94717 datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene coexpression network analysis was performed to find modules possibly involved in sepsis. A long noncoding RNA-microRNA-messenger RNA (lncRNA-miRNA-mRNA) network was constructed based on the findings. Single-cell analysis was performed. Human umbilical vein endothelial cells were treated with lipopolysaccharide (LPS) to create an model of sepsis for network verification. Reverse transcription-polymerase chain reaction, fluorescence hybridization, and luciferase reporter genes were used to verify the bioinformatic analysis. By integrating data from three GEO datasets, we successfully constructed a ceRNA network containing 18 lncRNAs, 7 miRNAs, and 94 mRNAs based on the ceRNA hypothesis. The lncRNA was found to be highly expressed in LPS-stimulated endothelial cells and may thus play a role in endothelial cell injury. Univariate and multivariate Cox analyses showed that only was an independent predictor of prognosis in sepsis. Overall, our findings indicated that the /hsa-miR-449c-5p/ ceRNA regulatory axis may play a role in the progression of sepsis. The sepsis ceRNA network, especially the /hsa-miR-449c-5p/ regulatory axis, is expected to reveal potential biomarkers and therapeutic targets for sepsis management.

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http://dx.doi.org/10.1089/gtmb.2023.0143DOI Listing

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